Search NASA⌕ Search

SEARCH · Search NASA

Results for “First Principles”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

On the applicability of the Redlich-Kister framework for viscosity estimation of molten halide salt mixtures

For molten halide salt mixtures already being utilized or under consideration for carbon-free energy production systems, it is crucial that their viscosity is well understood so that system thermal hydraulics can be reliably assessed. Because of the difficulty in accurately measuring molten halide viscosity and the sheer size of the matrix of possible higher order salt mixtures that may be of interest to the energy industry, there are several gaps in the quantified understanding of molten halide viscosity across this matrix. As such, both first-principles and semi-empirical modeling techniques may be crucial for rapidly assessing this broad, complex compositional domain. Herein, the Redlich-Kister framework is applied to assess the feasibility of broadly interpolating and estimating the viscosity of several pseudobinary and pseudoternary molten halide salt systems that may be of key interest to the energy industry. The framework is based on the assumption that an ideal component and a nonideal component collectively describe the viscosity as a function of composition and temperature for a given molten halide system. Three different ideal models were considered for the ideal component, including Grunburg-Nissan, Katti-Chaudhri, and Gambill methods. Regarding the pseudobinary interpolations, the Redlich-Kister models with either the Grunburg-Nissan or Katti-Chaudhri models as the ideal component resulted in either highly (average error less than 5%) or reasonably (average error less than 15%) accurate interpolations of pseudobinary halide viscosity; BeF 2 - or UF 4 -bearing salts tended to result in reasonably accurate interpolations, whereas other pseudobinary mixtures tended to show high accuracy. Regarding the pseudoternary extrapolations, the Redlich-Kister framework shows reasonable success at estimating the extent to which a pseudoternary system may indicate deviations from ideal Grunburg-Nissan mixing, where discrepancies with comparative experimental data generally stay within 30%. Finally, the primary reasons identified for such discrepancies are (1) inaccuracy in the underlying experimental data, (2) different complexation behavior in the higher order systems compared to the pseudobinary subsystems, and (3) extrapolation into temperatures too far out of the domain, which is valid for the underlying experimental data feeding the Redlich-Kister model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Machine learning enabled discovery of superhard and ultrahard carbon polymorphs

The demand for multifunctional materials has motivated the move from near-equilibrium materials to metastable i.e. out-of-equilibrium phases that can meet several desired target properties. The search for such metastable phases with exotic properties is non-trivial and often serendipitous. Inverse design approaches based on evolutionary search have been powerful tools, but such traditional searches have focused on identifying primarily stable and metastable materials with the lowest enthalpy. The inverse design of materials, with a focus on a desired property such as, for example, hardness is a challenging task because of the expensive computational cost involved in sampling multiple structures. The recent advances in machine learning have brought new powerful AI techniques to the forefront which can potentially revolutionize the inverse design and discovery of materials, especially metastable phases capable of meeting multifunctionality. Here, in this work, we develop and apply an automated reinforcement learning workflow for inverse design that integrates first principles physics and atomistic simulations with machine learning (ML), and high-performance computing to allow rapid exploration of the superhard and ultrahard metastable phases of Carbon. We demonstrate an automatic machine learning based inverse design workflow to map new undiscovered metastable states ranging from near equilibrium to those far-from-equilibrium that satisfy multiple property objectives, specifically bulk moduli, shear moduli and hardness. We create a comprehensive library of carbon stable and metastable phases with varying hardness and subsequently shortlist 10 top performing candidate carbon structures, including two newly reported phases, based on their hardness and characterize their temperature dependent mechanical properties. A neural network model is built using featurization of allotropes of carbon to predict the quasi-harmonic Gibbs free energies. The Gibbs free energies of the top performing phases are analyzed to get an estimate of the experimental synthesizability of these superhard and ultrahard carbon phases. In general, we show using machine learning based inverse design approaches how hitherto inaccessible metastable states can be identified and potentially synthesized to meet the demand for multifunctional materials.

Balasubramanian, Karthik [Univ. of Illinois, Chica↗
DOE OSTI2025

Hydrogen and water interactions with CrMnFeCoNi alloy from density functional theory calculations

High entropy alloys (HEAs) are a promising class of materials with remarkable mechanical and catalytic properties. Among these, the quinary CrMnFeCoNi alloy (also called “Cantor alloy”) has attracted considerable attention given its thermodynamic stability and remarkable mechanical properties under different temperatures. Given that various degradation mechanisms involve multiple contaminants, such as hydrogen and water in hydrogen embrittlement and surface poisoning, respectively, understanding their interactions with the Cantor alloy is critical for its practical applications as structural, nuclear, or hydrogen storage material. In this work, we perform first-principles calculations based on Density Functional Theory (DFT) to investigate such interactions when considering various microstructures, including bulk materials and those containing certain defects, such as grain boundaries, stacking faults, and vacancies. We also employ Global Sensitivity Analysis to identify the importance of different factors in the stability of the impurities. We find that the accuracy of the H formation energy is significantly affected by spin polarization and chemical short-range order. The study also identifies a strong tendency for hydrogen interstitials to segregate to Σ5(210)/[001] symmetric tilt grain boundary, even when H concentrations are high, suggesting that a certain type of grain boundaries acts as H sinks within the alloy. Further, this result is reinforced by the low formation energy of vacancy-hydrogen complexes, which can contain multiple hydrogen atoms. Finally, the surface reactivity analysis reveals that the adsorption energy of oxygen and hydroxyl groups is highly sensitive to the specific metal atom involved in the binding, with a clear preference for chromium atoms, which could have implications for the alloy’s oxidation and corrosion behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2025

CASM Monte Carlo: Calculations of the thermodynamic and kinetic properties of complex multicomponent crystals

Monte Carlo techniques play a central role in statistical mechanics approaches that connect macroscopic thermodynamic and kinetic properties to the electronic structure of a material. This paper describes the implementation of Monte Carlo techniques for the study of multicomponent crystalline materials within the Clusters Approach to Statistical Mechanics (CASM) software suite, and demonstrates their use in model systems to calculate free energies and kinetic coefficients, study phase transitions, and construct phase diagrams from first principles. Many crystal structures are complex, with multiple sublattices occupied by differing sets of chemical species, along with the presence of vacancies or interstitial species. This imposes constraints on concentration variables, the form of thermodynamic potentials, and the values of kinetic transport coefficients. The framework used by CASM to formulate thermodynamic potentials and kinetic transport coefficients accounting for arbitrarily complex crystal structures is presented and demonstrated with examples of increasing complexity. Additionally, an overview of the capabilities of the CASM software specific to Monte Carlo methods is given, and a new CASM software package is introduced, casm-flow, which helps automate the setup, submission, management, and analysis of Monte Carlo simulations.

Cluster expansion↗
DOE OSTI2025

A generalized and adaptable tensor-contraction-based cluster expansion formalism for multicomponent solids

Density functional theory (DFT)-based simulations of materials have first-principles accuracy, but are very computationally expensive. For simulating various properties of multi-component alloys, the cluster expansion (CE) technique has served as the standard workaround to improve computational efficiency. However, the standard CE technique is difficult to extend to exotic and/or low-symmetry lattices, often implemented via iteration over particular cluster types, which must be enumerated per lattice structure. In this work, we introduce the tensor cluster expansion (TCE), implemented in the open-source code tce-lib, which maps correlation functions to mixed tensor contractions, eliminating the need to iterate over cluster types and additionally making the calculation of correlation functions well-suited for massively parallel architectures like GPUs. We show that local interaction energies are an immediate consequence of the TCE formalism, yielding nearly $\mathcal{O}$(1) energy difference calculations. We then use this formalism to fit CE models for the TaW and CoNiCrFeMn systems, and use these models to respectively compute the enthalpy of mixing curve and Cowley short-range order parameters, showing excellent agreement with ground truth data.

Cluster expansion↗
DOE OSTI2025

Quasiparticle description of angle-resolved photoemission spectroscopy for SrCuO 2

SrCuO 2 has long been considered a near-archetypal realization of a quasi-one-dimensional (1D) system of interacting electrons with short-range interactions. Within this framework, experimental observations - interpreted through the lens of the 1D Hubbard model - suggest that electron and hole excitations decay into two types of (unphysical) collective bosonic modes: "spinons", which carry the spin degree of freedom, and "holons", which carry the charge degree of freedom. This model, known as spin-charge separation, is most directly evidenced by angle-resolved photoemission spectroscopy (ARPES), where a photo-induced hole decays into a continuum of these excitations. Here we present an alternative perspective grounded in first-principles, self-consistent, and parameter-free many-body perturbation theory. In this revised quasiparticle framework, ARPES can be understood as a one-body effect arising from mild disorder in a long-range antiferromagnetic ground state. the emergence of the so-called spinon branch arises naturally from spin disorder, the anomalous linewidths are accurately captured, and we provide a compelling explanation for the spectral weight observed at the non-magnetic zone boundary. This reinterpretation provides a unified explanation for key experimental signatures previously attributed to spin-charge separation, including features observed in optical conductivity. Additionally, we show that SrCuO 2 exhibits a nontrivial interchain coupling that significantly influences both its one-particle and two-particle spectral functions. By comparing the spectral features of SrCuO 2 with those of La 2 CuO 4 , we argue that SrCuO 2 shares notable similarities with the two-dimensional cuprates-both being rooted in a common CuO 4 plaquette-based molecular orbital framework.

1D cuprates↗
DOE OSTI2025

The microscopic mechanisms of high temperature oxidation of Haynes 282

Nickel-based superalloy finds widespread applications in aerospace and extreme environments. They are known for their high temperature oxidation resistance under extended periods. However, the oxide formation and evolution which sets the stages for the later parabolic oxidation kinetics is not fully understood. This paper aims to provide new insights into the transient stage oxidation mechanism and kinetics of a typical Ni-based superalloy (Haynes 282). While tracking the chemical and microstructural evolution under micrometer scale at 800°C, we show that the oxide scale and its grain boundary species change significantly during the initial stages of oxidation and can have a profound impact on the oxidation kinetics. Cr 2 O 3 forms initially at the grain boundary along with minor amount of Al 2 O 3 . Then, the grain boundary region is enriched with copious amounts TiO 2 while Cr migrates away from the grain boundary. A noticeable change in the isothermal oxidation kinetics observed likely results from a mechanistic change from uniform surface oxidation to preferential outward diffusion of Ti 4+ ions through the grain boundary. Through first-principles calculations combined with energy dispersive spectroscopy, we confirmed the preferential outward diffusion of Ti 4+ ions as the diffusion barrier is lower for Ti than Cr along the grain boundaries. In conclusion, these findings highlight the critical role of early-stage grain boundary oxidation dynamics in dictating the long-term oxidation resistance of Ni-based superalloys and provide a foundation for future strategies to enhance their performance in extreme environments.

DFT↗
DOE OSTI2025

Multiphase computational fluid dynamics modeling of reacting flows in absorption columns for carbon capture

First-principles derived computational fluid dynamics (CFD) simulations have been proposed as a fundamental tool for investigating solvent-based CO 2 absorption in packed columns due to their ability to accurately represent the underlying nonlinear, multiscale dynamics. Numerous studies have previously utilized such CFD simulations to investigate hydrodynamics of columns with structured and random packings by assessing the key hydrodynamic metrics such as the interfacial and wetted areas. While mapping such metrics for different conditions is essential to the optimization of absorption columns, it is not sufficient, as the CO 2 capture rate depends also on the coupled, nonlinear dynamics from the underlying chemical reaction kinetics, thermodynamics, and heat-transfer rates. In this work, we present detailed CFD simulation results augmented by incorporating the effects of interfacial physical mass transfer of CO 2 , heat release from chemical reaction kinetics, and thermophysical property variations from resulting temperature gradients. We demonstrate the applicability of the proposed approach in numerically assessing the performance of packed columns by evaluating key hydrodynamic quantities, CO 2 absorption rates, and temperature rise in a reference column with packings that are structurally similar to the Sulzer Mellapak™ 250.Y packing, for different solvent inflow velocities and temperatures. Predictions from simulation results are found to be consistent with the trends in experimental observations from the literature, suggesting that the predictive capabilities of the simulation framework can be leveraged to guide the future development of absorber-column designs and optimized process flowsheets.

Absorption columns↗
DOE OSTI2025

Resolving Lonsdaleite's decade-long controversy: Atomistic insights into a metastable diamond polymorph

Lonsdaleite, a theoretically proposed hexagonal diamond polymorph, has remained at the center of a five-decade scientific controversy since its 1967 identification. While some studies claim it exhibits superior hardness through compression-induced structural changes, others contend it is merely a stacking-faulted cubic diamond. Meteoritic samples and synthetic preparations have yielded conflicting evidence, with even advanced characterisation techniques like XRD and TEM failing to provide definitive proof. In this work, we employ first-principles density functional theory (DFT) and molecular dynamics (MD) simulations to generate unambiguous theoretical fingerprints through XRD, Raman, and SAED patterns that distinguish true Lonsdaleite from cubic diamond and its defective variants. Our atomistic approach quantifies the thermodynamic metastability of Lonsdaleite under realistic pressure-temperature conditions, reveals distinct spectral signatures through simulated Raman and resolves the structural ambiguity through generalised stacking fault energy analysis. By establishing clear criteria for definitive identification, this study provides long-awaited clarity to the Lonsdaleite debate while offering a robust computational framework for characterising metastable carbon phases in meteoritic, synthetic and industrial materials.

DFT↗
DOE OSTI2025

Thermal decomposition pathways of bulk electrolytes on vanadium oxide nanocrystals

The thermal stability of electrolytes at an elevated temperature induced by battery charge-discharge cycling is critical for the long cycling performance of a rechargeable battery. For many multivalent systems, such as rechargeable magnesium batteries, which offer great potential for high energy density and utilize earth-abundant resources, electrolyte instability and electrode surface passivation, arising from electrolyte decomposition, remain as major roadblocks. Understanding the electrolyte decomposition pathways at the electrode-electrolyte interface is essential to provide guidance in overcoming this challenge. In this work, in situ 13 C magic angle spinning nuclear magnetic resonance (MAS NMR) and first-principles calculations were used to investigate the thermal decomposition of the electrolyte in a system consisting of MgV 2 O 4 , a novel cathode for magnesium batteries, mixed with a bulk electrolyte consisting of magnesium bis(trifluoromethanesulfonyl)imide (Mg(TFSI) 2 ) in diglyme (G2). We show that significant electrolyte decomposition is observed in bulk 1.0 M Mg(TFSI) 2 in G2 mixed with nanometer sized MgV 2 O 4 powder at elevated temperatures. This observation is to mimic the possible thermal decomposition that might happen during battery cycling. We demonstrate that the MgV 2 O 4 surface is covered by a layer of decomposed G2 products. We conclude that the dominant reaction pathway for electrolyte decomposition is the thermal decomposition of the pure electrolytes at elevated temperatures, followed by adsorption of G2 decomposition products to the MgV 2 O 4 surface. The activation energy for the major decomposition pathway is obtained. In conclusion, this work highlights the importance of studying thermal decomposition of electrolytes for overall system stability and explores electrolyte stability at significantly elevated temperatures.

25 ENERGY STORAGE↗
DOE OSTI2024

Computing the solubility of argon and xenon in molten sodium chloride and potassium chloride salts

Molten salt reactors (MSRs) offer significant advancements in nuclear reactor safety and efficiency by operating at higher temperatures and lower pressures compared to traditional reactors. A critical aspect of MSR operation involves understanding the solubility of fission byproducts, particularly noble gases, in the molten salts used. This study employs molecular dynamics (MD) simulations to compute Henry’s law constants and enthalpies of solvation for argon and xenon in molten sodium chloride (NaCl) and potassium chloride (KCl). We developed a new pairwise potential for the noble gas and salt interactions based on first principles calculations. We then used this potential to calculate Henry’s law constants of the two gases in the molten salts, which were modeled using both a rigid ion model (RIM) and a polarizable ion model (PIM). The solubility calculations, performed using the Widom insertion method, show qualitative agreement with limited experimental data, highlighting the temperature dependence and greater solubility of both gases in KCl compared to NaCl. Additionally, free volume analysis elucidated the role of available space within the molten salts in governing solubility trends. Our findings suggest that PIM trajectories provide more reliable predictions for noble gas solubility than RIM due to their accurate density representation. Furthermore, these results enhance understanding of gas solubility in MSR environments, and the methods can be readily extended to other systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Reduced-dimension Bayesian optimization for model calibration of transient vapor compression cycles

Development and calibration of first-principles dynamic models of vapor compression cycles (VCCs) is of critical importance for applications that include control design and fault detection and diagnostics. Nevertheless, the inherent complexity of models that are represented by large systems of differential–algebraic equations leads to significant challenges for model calibration processes that utilize classical gradient-based methods. Bayesian optimization (BO) is a sample-efficient and gradient-free approach using a probabilistic surrogate model and optimal search over a feasible parameter space. Despite the benefits of BO in reducing computational costs, challenges remain in dealing with a high-dimensional calibration task resulting from a large set of parameters that have significant impacts on system behavior and need to be calibrated simultaneously. This paper presents a reduced-dimension BO framework for calibrating transient VCCs models where the calibration space is projected to a low-dimensional subspace for accelerating convergence of the solution algorithm and consequently reducing the number of transient simulations. The proposed approach was demonstrated via two case studies associated with different VCC applications where 10 parameters were calibrated in each case using laboratory measurements. The reduced-dimension BO framework only required 1 / 8 th of the iterations associated with a standard BO method that deals with high-dimensional calibration parameters for converged solutions and yielded comparable accuracy. Furthermore, both calibrated models revealed significant accuracy improvements compared to uncalibrated models.

Ma, Jiacheng↗
DOE OSTI2024

Structure and disorder resulting in ultralow thermal conductivity in the defect chalcopyrite AgInSnSe 4

Quaternary chalcogenides are attractive for a variety of technological fields of interest due to the diverse physical properties these materials possess. Herein, the structural and thermal properties of the disordered chalcopyrite AgInSnSe 4 are reported revealing a distinct relation between its structure and physical properties. Modeling of the experimental temperature-dependent thermal properties revealed an ultralow thermal conductivity (0.47 Wm -1 K -1 at room temperature) due to lattice anharmonicity, a low speed of sound and a low Debye temperature. Moreover, first principles electronic structure calculations revealed that the Ag-Se tetrahedra within the crystal structure possess relatively weak bonds due to occupied antibonding states from p-d orbital hybridization, which suppress the thermal conductivity. Here, in order to further quantify our findings, we extended our analyses to include comparisons with other ternary and quaternary adamantine materials, all of which possess a fourfold tetrahedral coordination of atoms, in revealing the origin of the thermal properties in AgInSnSe 4 .

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effect of Sn microalloying on the nucleation of L1 2 Al 3 Zr precipitates in a dilute aluminum-zirconium alloy

While L1 2 -Al 3 Zr nanoprecipitates provide a balance between strengthening and good electrical conductivity, the precipitation of L1 2 -Al 3 Zr in aluminum requires aggressive heat treatments. An improved age-hardening response was observed during isochronal aging of an Al-0.24Zr (wt%) alloy when microalloyed with Sn. A new mechanism termed Low melting point Element-Assisted Nucleation (LEAN) is proposed to explain the lower temperature nucleation of L1 2 -Al 3 Zr precipitates observed in this alloy based on the addition of a low melting point element, such as Sn. Characterization verified the first-principles density functional theory prediction that Zr and Sn atoms cluster during homogenization owing to the favorable binding energy of Zr-Sn-vacancy triplets. Direct microstructural observations revealed these clusters form Sn nanoprecipitates that assist the nucleation of L1 2 -Al 3 Zr at 200°C, where L1 2 -Al 3 Zr precipitation is not expected due to the low diffusivity of Zr atoms in Al. At higher temperatures (≳350°C), the acceleration of L1 2 -Al 3 Zr precipitation is driven by faster Zr diffusion in Al with Sn microalloying and the nuclei formed via the LEAN mechanism. In conclusion, this combination of mechanisms explains the improvement in age hardening through L1 2 -Al 3 Zr precipitation with Sn microalloying.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Surface intermediates identified using IR spectroscopy during the catalytic oxidation of C 2 H 6 on IrO 2 (1 1 0) at near-ambient pressures

Characterizing surface intermediates during catalysis is essential for developing mechanistic models of catalytic reactions and for identifying rate-controlling steps. Here, in this work, we used polarization-dependent reflection absorption infrared spectroscopy (PD-RAIRS) to investigate surface intermediates that form on IrO 2 (1 1 0) during the catalytic oxidation of C 2 H 6 at pressures near 0.5 Torr. Our results show that adsorbed CO and HCO 2 are the only intermediates detectable with PD-RAIRS across a wide range of temperatures and reactant compositions during complete C 2 H 6 oxidation, giving rise to dominant peaks at about 2093 and 1310 cm −1 , respectively. These assignments were corroborated by RAIRS measurements following CO and HCOOH adsorption in ultrahigh vacuum, RAIRS with C 2 H 6 – 18 O 2 mixtures during catalysis and vibrational frequencies and IR intensities computed using density functional theory. We find that increasing the C 2 H 6 mole fraction in the reaction mixture raises the CO surface coverage relative to HCO 2 , correlating with increasing catalytic oxidation rates. The formation of CO and HCO 2 surface species at temperatures well below catalytic ignition indicates that the overall rate of C 2 H 6 oxidation on IrO 2 (1 1 0) is governed by steps late in the reaction sequence, such as H 2 O formation, CO oxidation and HCO 2 dehydrogenation. These findings provide key insight into the mechanism of alkane oxidation on IrO 2 (1 1 0) and valuable input for first-principles microkinetic modeling.

Pope, Connor [Univ. of Florida, Gainesville, FL (U↗
DOE OSTI2025

Tunable broadband luminescence in lead-free hybrid copper halides

Metal halides are an important class of optoelectronic materials combining exceptional optical and electronic properties. An inherent advantage of metal halides is their solution synthesis and processability, which render them as low-cost and environmentally friendly materials for a range of applications from photovoltaics and photodetection to solid-state lighting (SSL). Here, in this study, we synthesized three previously unreported lead-free organic–inorganic hybrid copper halides: (OA) 4 CuX 5 (X = Br, I; OA + = C 8 H 17 NH 3+ , n-octylammonium cation) and (HA) 2 CuI 3 (HA + = C 6 H 13 NH 3 + , n-hexylammonium cation), all of which exhibit broadband emissions arising from self-trapped excitons (STEs). Among these compounds, (OA) 4 CuI 5 demonstrates tunable dual-band white-light emission with a high color rendering index value of 91 at room temperature. Temperature-dependent photoluminescence measurements and first-principles calculations reveal distinct behaviors between the two emission states in (OA) 4 CuI 5 . These findings highlight the potential of copper halide compounds for optoelectronic applications, particularly in the development of environmentally friendly solid-state lighting technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Back to functional hydrides: Effects of neutron-irradiated microstructure on hydrogen retention in yttrium hydride

Functional hydrides are promising candidates for advanced nuclear reactors, particularly in portable or transportable applications, due to their high hydrogen-retention capabilities, enabling efficient neutron moderation, and compact reactor design. However, hydrogen mobility in hydrides at elevated irradiation temperatures poses significant technological challenges, necessitating a comprehensive understanding of their irradiation behavior. Furthermore, this study investigated the microstructural and chemical stability of neutron-irradiated yttrium hydrides to assess their hydrogen-retention capacity. A targeted literature review was also conducted to contextualize neutron-irradiation effects on functional hydrides with regards to structural stability and hydrogen retention. Experimental characterizations revealed that, at high temperatures, irradiated hydrides retained their phase stability, which was likely enhanced by irradiation-induced microstructure evolution. Notably, an amorphous yttrium and oxygen -rich surface layer was present at the free surface of the hydride. Its thickness decreased while a continuous crystalline Y-O-rich layer was formed with increasing neutron damage. Additionally, the number density of dislocation loops and cavities generally increased as a function of neutron dose. First-principles calculations of hydrogen behavior within yttrium vacancy clusters in yttrium hydrides demonstrated vacancy-size-dependent hydrogen stability and configuration, highlighting the role of vacancy geometry in regulating hydrogen retention. Thus, the presence of irradiation-induced dislocation loops and cavities were hypothesized to improve hydrogen retention. Collectively, these findings advance the understanding of hydride behavior under neutron irradiation as well as their technological readiness for portable or transportable nuclear reactors.

Defect clusters↗
DOE OSTI2025

Effect of high scandium doping in barium zirconate on nickel diffusion and performance of proton-conducting solid oxide electrolyzer cells

Proton-conducting solid oxide electrolyzer cells (p-SOECs) are emerging but promising technologies for hydrogen production. However, due to the lack of a robust electrolyte, p-SOECs struggle simultaneously to display high performance, Faradaic efficiency, and durability. Motivated by its high proton concentrations and stability as a barium zirconate, we have investigated BaZr 0.6 Sc 0.4 O 3-δ (BZSc40) as a potential next-generation p-SOEC electrolyte. Here, we found elevated levels of NiO diffusion through BZSc40 electrolytes during high-temperature sintering, attributed to the large oxygen vacancy concentrations present in BZSc40, as revealed by first-principle computational results. Controlling NiO diffusion is critical, as it can facilitate densification and grain size growth, but it may also detrimentally impact performance by causing electronic leakage. By optimizing sintering temperature when fabricating BZSc40 cells, we successfully controlled NiO diffusion, achieving sufficient electrolyte densification along with high performance and Faradaic efficiency. BZSc40 cells reached −0.99 A/cm 2 at 1.3 V and 600 °C and exhibited enhanced durability with a 3.37 mV/kh degradation rate at −0.8 A/cm 2 over a 200-h testing period. BZSc40 electrolytes demonstrated superior performance over BaZr 0.8 Y 0.2 O 3-δ (BZY20). In addition to elevated current densities and grain sizes, BZSc40 cells achieved Faradaic efficiencies of 76 % compared to 54 % for BZY20 at −0.2 A/cm 2 and 600 °C. This work lays the foundation for BZSc40 as a potential electrolyte due to its advantages over BZY20 while demonstrating the significance of controlling NiO diffusion when fabricating p-SOECs.

Electrolyzer↗